1. Field of the Invention
The present invention relates generally to control systems, and more particularly, to control systems which employ internal-model based control to account for time delays of a process being controlled.
2. State of the Art
Control systems which employ internal model-based control are known. For example, U.S. Pat. No. 5,121,332 (Balakrishnan et al) discloses a control system wherein an internal model-based control is used. Further, a document entitled "A Linear Programming Approach To Constrained Multivariable Process Control" by C. Brosilow and G. Q. Zhao (Control and Dynamic Systems, Ed. by C. T. Leondes, Vol. 27: System Identification and Adaptive Control, Academic Press, Inc., 1988) discloses a control system wherein an internal model-based control is used. The control systems described in these documents use an internal model control (MC) structure, such as the known Smith Predictor, for controlling processes with long time delays.
Controlled processes which incorporate long time delays can be considered to include two general components: (1) a dynamic gain, or transfer function, component of the overall process (absent any process time delays); and (2) the time delay component of the process. When a setpoint reference is applied directly to the process in an open-loop fashion, the process often responds with a time delay and with a steady-state amplitude different from the setpoint commanded. This is known as the bias problem.
Prior to the inclusion of internal model-based control, the bias problem was addressed by including direct feedback of the output signal to a comparator which also received the setpoint reference. The error between the setpoint reference and the output was then supplied to a controller having an integration function. This integration function was effective in erasing bias of the output signal relative to the input signal. However, for processes having long time delays, the error signal produced by the comparator existed for significant periods of time. The integration of the error signal over this relatively long period of time resulted in the process overshooting the desired setpoint reference, leading to an unstable, oscillatory output.
Internal model-based control was developed to address the unstable, oscillatory output associated with the use of direct feedback in a process control. Referring to FIG. 1, a controller which incorporates a Smith Predictor as an internal model-based controller is illustrated. In the FIG. 1 illustration, a setpoint reference 102, labelled "r", is supplied to a three input comparator 104. An output of the comparator 104 is supplied to a controller 106. The controller includes the integration feature described previously for addressing bias, and produces an output control signal labelled "u".
The control signal "u" is supplied to the control process represented by dashed lines 108. As mentioned previously, the process 108 can be considered to include two components: (1) the dynamic gain, or transfer function, component 110 labeled as a gain "G"; and a delay component 112 labelled "D". Because the process 108 is a real time process which is susceptible to environmental disturbances, an output from the dynamic gain component 110 is illustrated as being input to an adder 115 which receives an external disturbance component 114, labelled "d". The process output is a controlled variable labelled "y".
The components described above with respect to FIG. 1 constitute a conventional open loop control process. Prior to the use of a Smith Predictor with internal model-based control, the output signal "y" would constitute the feedback signal compared with the setpoint reference "r" to generate an error signal for controlling the process. However, as mentioned previously, such use of direct feedback may result in an unstable and oscillatory output signal "y".
To address the foregoing instabilities, the FIG. 1 illustration includes a Smith Predictor, configured as an internal model 116 of the process 108. The internal model 116 is a theoretical model of the process 108. The internal model 116 is illustrated as including two components: (1) a model dynamic gain component 118 labelled "G"; and (2) a model delay component 120 labelled "D". The model dynamic gain component 118 produces a predicted value "y.sub.pred " of the control variable "y". This predicted value constitutes a prediction of the value of "y" a set number of time units (e.g., D time units) into the future.
The model delay component 120 models the delay component 112, and produces an output labelled "y" which is intended to be very close to the process output "y". In practice, where the external disturbance component "d" is negligible, the internal model 116 can be empirically developed to produce an output "y" which is very close to the actual process output "y". Thus, the control signal "u" is supplied to two portions of the FIG. 1 illustration: (1) the actual process being controlled; and (2) the internal model, which receives the control signal in parallel with the process 108.
To address control system instabilities, an inner feedback loop 122 is provided without inclusion of time delay model D. This inner feedback loop supplies the predicted value "y.sub.pred ", representing a prediction of "y" D time units into the future, back to the comparator 104 where it is subtractively combined with the setpoint reference 102. Because the signal "y.sub.pred " is not supplied through the model delay component 120, it tracks changes in the control signal "u" very quickly. Thus, the inner feedback loop 122 supplies feedback almost immediately for correcting the control signal "u" and thereby avoiding oscillation in the control signal due to overshoot caused by time delay.
The FIG. 1 controller also includes an outer feedback loop 124 which feeds back an error, or mismatch signal, labelled .epsilon.. The mismatch signal .epsilon. is generated by comparing the actual process output "y" and the predicted value "y" in a comparator 126. The mismatch signal .epsilon. is supplied to a low pass filter 128. The low pass filter 128 is configured with a cutoff frequency that corresponds to the desired bandwidth of process operation, and produces a filtered mismatch signal labelled .epsilon.. The filtered mismatch signal .epsilon. is supplied to a comparator 130, wherein it is subtractively combined with a mismatch reference signal.
As those skilled in the art will appreciate, during ideal conditions, the internal model 116 will correspond identically to the process 108. As such, changes in the control signal "u" will be reflected equally in changes of the process output "y" and the predicted process output "y". The mismatch signal .epsilon. will therefore ideally be zero during operation, as will the output from comparator 130, provided that the external disturbance "d" does not exist.
The control system of FIG. 1 works well if the internal model 116 is closely matched to the process and if there are no external disturbances "d". That is, the inner loop prevents the buildup of oscillations, while the outer feedback loop 124 corrects for long term (low frequency) mismatches between the internal model 116 and the actual process 108. However, difficulties may arise when external disturbances, as represented by the external disturbance component "d", exist. In this case, the mismatch signal .epsilon. will take on a value which is not due to inaccuracies in the internal model 116, but rather to periodic and/or random disturbances to the process. Although long term (slow) disturbances can be addressed effectively with the FIG. 1 controller, fast varying external disturbances cannot be properly addressed. In fact, they may be amplified by the feedback loop.
More particularly, values of .epsilon. due to fast changing external disturbances result in the output from comparator 130 taking on a value which is intended to cancel the effect of the external disturbance component "d". However, because of the time delay included in the process 108 and the external model 116, the outer feedback loop can only correct for very low frequency disturbances. High frequency disturbances will likely take on (very) different values by the time the corrective control actions show effect on the delayed response. The net effect may be an amplification of the disturbance "d".
Although the aforementioned Broslow et al document describes a control system which includes a "predictor" in a feedback path, the system described in this document does not adequately address the problems described above. Rather, at best, this document describes using currently observed external disturbances as a feedback, and making an assumption that these disturbances will not change over the time period associated with the prediction interval. In other words, the "predictor" is not a predictor at all, but rather, uses the current disturbance as an estimate of what a future disturbance will be.
Accordingly, it would be desirable to develop a control apparatus and method which includes internal model-based control to account for long process delays, while effectively taking any external disturbance components into account in a manner which produces a stable, predictable output.